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* feat(insightface): add antispoofing (liveness) detection
Light up the anti_spoofing flag that was parked during the first pass.
Both FaceVerify and FaceAnalyze now run the Silent-Face MiniFASNetV2 +
MiniFASNetV1SE ensemble (~4 MB, Apache 2.0, CPU <10ms) when the flag is
set. Failed liveness on either image vetoes FaceVerify regardless of
embedding similarity. Every insightface* gallery entry now ships the
MiniFASNet ONNX weights so existing packs light up after reinstall.
Setting the flag against a model without the MiniFASNet files returns
FAILED_PRECONDITION (HTTP 412) with a clear install message — no
silent is_real=false.
FaceVerifyResponse gained per-image img{1,2}_is_real and
img{1,2}_antispoof_score (proto 9-12); FaceAnalysis's existing
is_real/antispoof_score fields are now populated. Schema fields are
pointers so they are fully absent from the JSON response when
anti_spoofing was not requested — avoids collapsing "not checked" with
"checked and fake" under Go's omitempty on bool.
Validated end-to-end over HTTP against a local install:
- verify + anti_spoofing, both real -> verified=true, score ~0.76
- verify + anti_spoofing, img2 spoof -> verified=false, img2_is_real=false
- analyze + anti_spoofing -> is_real and score per face
- flag against model without MiniFASNet -> HTTP 412 fail-loud
Assisted-by: Claude:claude-opus-4-7 go vet
* test(insightface): wire test target into test-extra
The root Makefile's `test-extra` already runs
`$(MAKE) -C backend/python/insightface test`, but the backend's
Makefile never defined the target — so the command silently errored
and the suite was never executed in CI. Adding the two-line target
(matching ace-step/Makefile) hooks `test.sh` → `runUnittests` →
`python -m unittest test.py`, which discovers both the pre-existing
engine classes (InsightFaceEngineTest, OnnxDirectEngineTest) and the
new AntispoofingTest. Each class skips gracefully when its weights
can't be downloaded from a network-restricted runner.
Assisted-by: Claude:claude-opus-4-7
* test(insightface): exercise antispoofing in e2e-backends (both paths)
Add a `face_antispoof` capability to the Ginkgo e2e suite and extend
the existing FaceVerify + FaceAnalyze specs with liveness assertions
covering BOTH paths:
real fixture -> is_real=true, score>0, verified stays true
spoof fixture -> is_real=false, verified vetoed to false
The spoof fixture is upstream's own `image_F2.jpg` (via the yakhyo
mirror) — verified locally against the MiniFASNetV2+V1SE ensemble to
classify as is_real=false with score ~0.013. That makes the assertion
deterministic across CI runs; synthetic/derived spoofs fool the model
unpredictably and would be flaky.
Makefile wires it up end-to-end:
- New INSIGHTFACE_ANTISPOOF_* cache dir + two ONNX downloads with
pinned SHAs, matching the gallery entries.
- insightface-antispoof-models target shared by both backend configs.
- FACE_SPOOF_IMAGE_URL passed via BACKEND_TEST_FACE_SPOOF_IMAGE_URL.
- Both e2e targets (buffalo-sc + opencv) now:
* depend on insightface-antispoof-models
* pass antispoof_v2_onnx / antispoof_v1se_onnx in BACKEND_TEST_OPTIONS
* include face_antispoof in BACKEND_TEST_CAPS
backend_test.go adds the new capability constant and a faceSpoofFile
fixture resolved the same way as faceFile1/2/3. Spoof assertions are
gated on both capFaceAntispoof AND faceSpoofFile being set, so a test
config that omits the spoof fixture degrades gracefully to "real path
only" instead of failing.
Assisted-by: Claude:claude-opus-4-7 go vet
433 lines
16 KiB
Go
433 lines
16 KiB
Go
package schema
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import (
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"encoding/json"
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"time"
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gopsutil "github.com/shirou/gopsutil/v3/process"
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)
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type BackendMonitorRequest struct {
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BasicModelRequest
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}
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type TokenMetricsRequest struct {
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BasicModelRequest
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}
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type BackendMonitorResponse struct {
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MemoryInfo *gopsutil.MemoryInfoStat
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MemoryPercent float32
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CPUPercent float64
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}
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type GalleryResponse struct {
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ID string `json:"uuid"`
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StatusURL string `json:"status"`
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EstimatedVRAMBytes uint64 `json:"estimated_vram_bytes,omitempty"`
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EstimatedVRAMDisplay string `json:"estimated_vram_display,omitempty"`
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EstimatedSizeBytes uint64 `json:"estimated_size_bytes,omitempty"`
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EstimatedSizeDisplay string `json:"estimated_size_display,omitempty"`
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}
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type VideoRequest struct {
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BasicModelRequest
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Prompt string `json:"prompt" yaml:"prompt"` // text description of the video to generate
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NegativePrompt string `json:"negative_prompt" yaml:"negative_prompt"` // things to avoid in the output
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StartImage string `json:"start_image" yaml:"start_image"` // URL or base64 of the first frame
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EndImage string `json:"end_image" yaml:"end_image"` // URL or base64 of the last frame
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Width int32 `json:"width" yaml:"width"` // output width in pixels
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Height int32 `json:"height" yaml:"height"` // output height in pixels
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NumFrames int32 `json:"num_frames" yaml:"num_frames"` // total number of frames to generate
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FPS int32 `json:"fps" yaml:"fps"` // frames per second
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Seconds string `json:"seconds,omitempty" yaml:"seconds,omitempty"` // duration in seconds (alternative to num_frames)
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Size string `json:"size,omitempty" yaml:"size,omitempty"` // WxH shorthand (e.g. "512x512")
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InputReference string `json:"input_reference,omitempty" yaml:"input_reference,omitempty"` // reference image or video URL
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Seed int32 `json:"seed" yaml:"seed"` // random seed for reproducibility
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CFGScale float32 `json:"cfg_scale" yaml:"cfg_scale"` // classifier-free guidance scale
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Step int32 `json:"step" yaml:"step"` // number of diffusion steps
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ResponseFormat string `json:"response_format" yaml:"response_format"` // output format (url or b64_json)
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}
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// @Description TTS request body
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type TTSRequest struct {
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BasicModelRequest
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Input string `json:"input" yaml:"input"` // text input
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Voice string `json:"voice" yaml:"voice"` // voice audio file or speaker id
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Backend string `json:"backend" yaml:"backend"` // backend engine override
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Language string `json:"language,omitempty" yaml:"language,omitempty"` // (optional) language to use with TTS model
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Format string `json:"response_format,omitempty" yaml:"response_format,omitempty"` // (optional) output format
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Stream bool `json:"stream,omitempty" yaml:"stream,omitempty"` // (optional) enable streaming TTS
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SampleRate int `json:"sample_rate,omitempty" yaml:"sample_rate,omitempty"` // (optional) desired output sample rate
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}
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// @Description VAD request body
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type VADRequest struct {
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BasicModelRequest
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Audio []float32 `json:"audio" yaml:"audio"` // raw audio samples as float32 PCM
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}
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type VADSegment struct {
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Start float32 `json:"start" yaml:"start"`
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End float32 `json:"end" yaml:"end"`
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}
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type VADResponse struct {
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Segments []VADSegment `json:"segments" yaml:"segments"`
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}
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type StoreCommon struct {
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Backend string `json:"backend,omitempty" yaml:"backend,omitempty"`
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}
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type StoresSet struct {
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Store string `json:"store,omitempty" yaml:"store,omitempty"`
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Keys [][]float32 `json:"keys" yaml:"keys"`
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Values []string `json:"values" yaml:"values"`
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StoreCommon
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}
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type StoresDelete struct {
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Store string `json:"store,omitempty" yaml:"store,omitempty"`
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Keys [][]float32 `json:"keys"`
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StoreCommon
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}
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type StoresGet struct {
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Store string `json:"store,omitempty" yaml:"store,omitempty"`
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Keys [][]float32 `json:"keys" yaml:"keys"`
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StoreCommon
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}
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type StoresGetResponse struct {
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Keys [][]float32 `json:"keys" yaml:"keys"`
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Values []string `json:"values" yaml:"values"`
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}
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type StoresFind struct {
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Store string `json:"store,omitempty" yaml:"store,omitempty"`
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Key []float32 `json:"key" yaml:"key"`
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Topk int `json:"topk" yaml:"topk"`
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StoreCommon
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}
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type StoresFindResponse struct {
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Keys [][]float32 `json:"keys" yaml:"keys"`
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Values []string `json:"values" yaml:"values"`
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Similarities []float32 `json:"similarities" yaml:"similarities"`
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}
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type NodeData struct {
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Name string
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ID string
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TunnelAddress string
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ServiceID string
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LastSeen time.Time
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}
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func (d NodeData) IsOnline() bool {
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now := time.Now()
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// if the node was seen in the last 40 seconds, it's online
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return now.Sub(d.LastSeen) < 40*time.Second
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}
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type P2PNodesResponse struct {
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LlamaCPPNodes []NodeData `json:"llama_cpp_nodes" yaml:"llama_cpp_nodes"`
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FederatedNodes []NodeData `json:"federated_nodes" yaml:"federated_nodes"`
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MLXNodes []NodeData `json:"mlx_nodes" yaml:"mlx_nodes"`
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}
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type SysInfoModel struct {
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ID string `json:"id"`
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}
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type SystemInformationResponse struct {
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Backends []string `json:"backends"` // available backend engines
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Models []SysInfoModel `json:"loaded_models"` // currently loaded models
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}
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type DetectionRequest struct {
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BasicModelRequest
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Image string `json:"image"` // URL or base64-encoded image to analyze
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Prompt string `json:"prompt,omitempty"` // Text prompt (for SAM 3 PCS mode)
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Points []float32 `json:"points,omitempty"` // Point coordinates as [x,y,label,...] triples (label: 1=pos, 0=neg)
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Boxes []float32 `json:"boxes,omitempty"` // Box coordinates as [x1,y1,x2,y2,...] quads
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Threshold float32 `json:"threshold,omitempty"` // Detection confidence threshold
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}
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type DetectionResponse struct {
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Detections []Detection `json:"detections"`
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}
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type Detection struct {
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X float32 `json:"x"`
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Y float32 `json:"y"`
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Width float32 `json:"width"`
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Height float32 `json:"height"`
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ClassName string `json:"class_name"`
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Confidence float32 `json:"confidence,omitempty"`
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Mask string `json:"mask,omitempty"` // base64-encoded PNG segmentation mask
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}
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// ─── Face recognition ──────────────────────────────────────────────
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//
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// FacialArea describes a bounding box for a detected face.
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type FacialArea struct {
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X float32 `json:"x"`
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Y float32 `json:"y"`
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W float32 `json:"w"`
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H float32 `json:"h"`
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}
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// FaceVerifyRequest compares two images to decide whether they depict
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// the same person. Img1 and Img2 accept URL, base64, or data-URI.
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type FaceVerifyRequest struct {
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BasicModelRequest
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Img1 string `json:"img1"`
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Img2 string `json:"img2"`
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Threshold float32 `json:"threshold,omitempty"`
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AntiSpoofing bool `json:"anti_spoofing,omitempty"`
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}
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type FaceVerifyResponse struct {
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Verified bool `json:"verified"`
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Distance float32 `json:"distance"`
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Threshold float32 `json:"threshold"`
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Confidence float32 `json:"confidence"`
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Model string `json:"model"`
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Img1Area FacialArea `json:"img1_area"`
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Img2Area FacialArea `json:"img2_area"`
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ProcessingTimeMs float32 `json:"processing_time_ms,omitempty"`
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// Liveness fields are only populated when the request set
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// anti_spoofing=true. Pointers keep them fully absent from the
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// JSON response otherwise, so callers can tell "not checked"
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// apart from "checked and fake" (which would collapse to zero
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// values with plain bool+omitempty).
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Img1IsReal *bool `json:"img1_is_real,omitempty"`
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Img1AntispoofScore *float32 `json:"img1_antispoof_score,omitempty"`
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Img2IsReal *bool `json:"img2_is_real,omitempty"`
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Img2AntispoofScore *float32 `json:"img2_antispoof_score,omitempty"`
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}
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// FaceAnalyzeRequest asks the backend for demographic attributes on
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// every face detected in Img.
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type FaceAnalyzeRequest struct {
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BasicModelRequest
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Img string `json:"img"`
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Actions []string `json:"actions,omitempty"` // subset of {"age","gender","emotion","race"}
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AntiSpoofing bool `json:"anti_spoofing,omitempty"`
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}
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type FaceAnalyzeResponse struct {
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Faces []FaceAnalysis `json:"faces"`
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}
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type FaceAnalysis struct {
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Region FacialArea `json:"region"`
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FaceConfidence float32 `json:"face_confidence"`
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Age float32 `json:"age,omitempty"`
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DominantGender string `json:"dominant_gender,omitempty"`
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Gender map[string]float32 `json:"gender,omitempty"`
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DominantEmotion string `json:"dominant_emotion,omitempty"`
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Emotion map[string]float32 `json:"emotion,omitempty"`
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DominantRace string `json:"dominant_race,omitempty"`
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Race map[string]float32 `json:"race,omitempty"`
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// Liveness fields — see FaceVerifyResponse for why these are pointers.
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IsReal *bool `json:"is_real,omitempty"`
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AntispoofScore *float32 `json:"antispoof_score,omitempty"`
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}
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// FaceEmbedRequest extracts a face embedding from an image. Distinct
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// from /v1/embeddings (which is OpenAI-compatible and text-only); this
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// endpoint accepts URL / base64 / data-URI image inputs.
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type FaceEmbedRequest struct {
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BasicModelRequest
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Img string `json:"img"`
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}
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type FaceEmbedResponse struct {
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Embedding []float32 `json:"embedding"`
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Dim int `json:"dim"`
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Model string `json:"model,omitempty"`
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}
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// FaceRegisterRequest enrolls a face into the 1:N recognition store.
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type FaceRegisterRequest struct {
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BasicModelRequest
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Img string `json:"img"`
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Name string `json:"name"`
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Labels map[string]string `json:"labels,omitempty"`
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Store string `json:"store,omitempty"` // vector store model; empty = local-store default
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}
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type FaceRegisterResponse struct {
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ID string `json:"id"`
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Name string `json:"name"`
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RegisteredAt time.Time `json:"registered_at"`
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}
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// FaceIdentifyRequest runs 1:N recognition: embed the probe and
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// return the top-K nearest registered faces.
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type FaceIdentifyRequest struct {
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BasicModelRequest
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Img string `json:"img"`
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TopK int `json:"top_k,omitempty"`
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Threshold float32 `json:"threshold,omitempty"` // optional cutoff on distance
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Store string `json:"store,omitempty"`
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}
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type FaceIdentifyResponse struct {
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Matches []FaceIdentifyMatch `json:"matches"`
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}
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type FaceIdentifyMatch struct {
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ID string `json:"id"`
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Name string `json:"name"`
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Labels map[string]string `json:"labels,omitempty"`
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Distance float32 `json:"distance"`
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Confidence float32 `json:"confidence"`
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Match bool `json:"match"` // true when distance <= threshold
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}
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// FaceForgetRequest removes a previously-registered face by ID.
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type FaceForgetRequest struct {
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BasicModelRequest
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ID string `json:"id"`
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Store string `json:"store,omitempty"`
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}
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// ─── Voice (speaker) recognition ───────────────────────────────────
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//
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// VoiceVerifyRequest compares two audio clips and reports whether they
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// were spoken by the same speaker. Audio1/Audio2 accept URL, base64,
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// or data-URI (the HTTP layer materialises the bytes to a temp file
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// before calling the gRPC backend).
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type VoiceVerifyRequest struct {
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BasicModelRequest
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Audio1 string `json:"audio1"`
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Audio2 string `json:"audio2"`
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Threshold float32 `json:"threshold,omitempty"`
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AntiSpoofing bool `json:"anti_spoofing,omitempty"`
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}
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type VoiceVerifyResponse struct {
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Verified bool `json:"verified"`
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Distance float32 `json:"distance"`
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Threshold float32 `json:"threshold"`
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Confidence float32 `json:"confidence"`
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Model string `json:"model"`
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ProcessingTimeMs float32 `json:"processing_time_ms,omitempty"`
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}
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// VoiceAnalyzeRequest asks the backend for demographic attributes
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// (age, gender, emotion) inferred from the audio clip.
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type VoiceAnalyzeRequest struct {
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BasicModelRequest
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Audio string `json:"audio"`
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Actions []string `json:"actions,omitempty"` // subset of {"age","gender","emotion"}
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}
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type VoiceAnalyzeResponse struct {
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Segments []VoiceAnalysis `json:"segments"`
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}
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type VoiceAnalysis struct {
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Start float32 `json:"start"`
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End float32 `json:"end"`
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Age float32 `json:"age,omitempty"`
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DominantGender string `json:"dominant_gender,omitempty"`
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Gender map[string]float32 `json:"gender,omitempty"`
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DominantEmotion string `json:"dominant_emotion,omitempty"`
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Emotion map[string]float32 `json:"emotion,omitempty"`
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}
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// VoiceEmbedRequest extracts a speaker embedding from an audio clip.
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// Distinct from /v1/embeddings (OpenAI-compatible, text-only) — this
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// endpoint accepts URL / base64 / data-URI audio inputs.
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type VoiceEmbedRequest struct {
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BasicModelRequest
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Audio string `json:"audio"`
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}
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type VoiceEmbedResponse struct {
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Embedding []float32 `json:"embedding"`
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Dim int `json:"dim"`
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Model string `json:"model,omitempty"`
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}
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// VoiceRegisterRequest enrolls a speaker into the 1:N identification store.
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type VoiceRegisterRequest struct {
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BasicModelRequest
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Audio string `json:"audio"`
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Name string `json:"name"`
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Labels map[string]string `json:"labels,omitempty"`
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Store string `json:"store,omitempty"`
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}
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type VoiceRegisterResponse struct {
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ID string `json:"id"`
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Name string `json:"name"`
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RegisteredAt time.Time `json:"registered_at"`
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}
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// VoiceIdentifyRequest runs 1:N recognition: embed the probe and
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// return the top-K nearest registered speakers.
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type VoiceIdentifyRequest struct {
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BasicModelRequest
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Audio string `json:"audio"`
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TopK int `json:"top_k,omitempty"`
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Threshold float32 `json:"threshold,omitempty"`
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Store string `json:"store,omitempty"`
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}
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type VoiceIdentifyResponse struct {
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Matches []VoiceIdentifyMatch `json:"matches"`
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}
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type VoiceIdentifyMatch struct {
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ID string `json:"id"`
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Name string `json:"name"`
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Labels map[string]string `json:"labels,omitempty"`
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Distance float32 `json:"distance"`
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Confidence float32 `json:"confidence"`
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Match bool `json:"match"`
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}
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// VoiceForgetRequest removes a previously-registered speaker by ID.
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type VoiceForgetRequest struct {
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BasicModelRequest
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ID string `json:"id"`
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Store string `json:"store,omitempty"`
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}
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type ImportModelRequest struct {
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URI string `json:"uri"`
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Preferences json.RawMessage `json:"preferences,omitempty"`
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}
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// KnownBackend describes a backend that the importer knows about.
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// Used by GET /backends/known to populate the import form dropdown.
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type KnownBackend struct {
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Name string `json:"name"`
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Modality string `json:"modality"`
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AutoDetect bool `json:"auto_detect"`
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Description string `json:"description,omitempty"`
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// Installed is true when the backend is currently present on disk — i.e. it
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// appears in gallery.ListSystemBackends(systemState). Importer-registered or
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// curated pref-only backends default to false unless they also show up on
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// disk. The import form uses this to warn users that submitting an import
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// may trigger an automatic backend download.
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Installed bool `json:"installed"`
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}
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// SettingsResponse is the response type for settings API operations
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type SettingsResponse struct {
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Success bool `json:"success"`
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Error string `json:"error,omitempty"`
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Message string `json:"message,omitempty"`
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}
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